Abstract only Background: Perfusion MRI may be used to reveal permeability changes reflective of blood-brain barrier derangements that predate hemorrhagic transformation (HT) in acute ischemic stroke. We conducted a multicenter observational study to compare and validate these novel T2*-permeability MRI measures as predictors of hemorrhage, deriving a predictive model for use with acute stroke therapies. Methods: Dynamic T2*-weighted perfusion MRI source images routinely obtained in the setting of acute ischemic stroke were collected from four academic medical centers. Post-processing was used to generate six previously described permeability parameters including contrast slope (CS), final contrast (FC), maximum peak bolus concentration (MPB), peak bolus area (PB), relative recirculation (rR), and %Recovery (%R). Clinical data including baseline demographics, medical history, lab values and treatment details were utilized to develop a predictive model for HT, combined with these novel permeability measures. The multivariate predictive model was evaluated using a 10-fold cross-validation to measure its generalization power on new patients. Results: Among 263 acute ischemic stroke patients analyzed in this large, multicenter collaborative imaging study, mean age was 69±15 years, 58.2% were women and baseline median NIHSS was 10 (range, 0-40). T2*-MRI sequences were acquired as part of routine imaging evaluation at a median of 214 minutes (range, 33-1440) from symptom onset. Treatments included IV tPA alone in 49%, endovascular recanalization therapies alone in 21.2%, and both in 10.4%. Overall, HT on GRE at 24 hours was observed in 84 (31.9%), including 34 HI1, 30 HI2, 9 PH1 and 11 PH2. More severe baseline NIHSS (r= 0.25, p<0.01) predicted HT at 24 hours. Individual T2*-permeability parameters exhibited positive predictive values (PPV) for HT ranging from 79-82% with negative predictive values (NPV) ranging from 70-78%. An automated predictive model integrating clinical data and all 6 multiparametric permeability measures exhibited PPV of 80% and NPV of 73% for HT at 24 hours. Conclusions: Permeability indices on dynamic T2*-weighted MRI routinely acquired for perfusion imaging in acute ischemic stroke can accurately predict HT using an automated predictive model. This novel automated predictive model may be used to refine treatment decisions in acute stroke.